Open Jarvis: making local LLMs work as agents

This post introduces Open Jarvis, a new framework for local LLM agents that decouples the harness from the model. It details a five-primitive configurable spec (Intelligence, Engine, Agent Logic, Tools & Memory, Learning) and demonstrates how LLM-guided spec search can retune harnesses for local models, recovering performance lost when swapping from cloud to local LLMs. It provides concrete benchmarks and cost comparisons for running local models on Lambda's HGX B200 instances, showing significant cost and latency advantages over cloud models.